Boxplots - Additional Improvements

library(tidyverse)
library(ggstatsplot)
library(gapminder)
library(ggforce)
library(Hmisc)
library(plotly)
library(patchwork)

df <- gapminder

table(df$continent)

## 
##   Africa Americas     Asia   Europe  Oceania 
##      624      300      396      360       24

df <- df %>%
  filter(year==2007 & !(continent %in% c("Oceania"))) %>%
  select(country,continent,lifeExp)

df$continent <- reorder(df$continent, df$lifeExp, median)

df$continent <- droplevels(df$continent)

table(df$continent)

## 
##   Africa     Asia Americas   Europe 
##       52       33       25       30

p1 <- df %>%
  ggplot(aes(x=continent,y=lifeExp,fill=continent)) + 
  geom_boxplot(alpha=0.75,show.legend=TRUE) + 
  geom_violin(alpha=0.25,show.legend=FALSE) + 
  labs(x="Continent",y="Life expectancy",title="Life Expectancy by Continent",caption= "Source: gapminder data set") +
  scale_fill_brewer(palette="Set1") + 
  theme_minimal(base_family = "Times New Roman",base_size=14) + 
  theme(plot.title = element_text(hjust=0.5,
                                  face="bold"),
        axis.title.x = element_text(face="italic"),
        axis.title.y =element_text(face="italic"),
        plot.caption =  element_text(face="italic")) + 
  ggpubr::bgcolor("#FEFEFA")

p1

continent_count <- df%>%
  group_by(continent)%>%
  count()

p2 <- df %>%
  ggplot(aes(x=continent,y=lifeExp,fill=continent)) + 
  geom_boxplot(alpha=0.75,show.legend = TRUE) + 
  #geom_violin(alpha=0.25,show.legend=FALSE,adjust=0.75) + 
  geom_dotplot(binaxis = "y",
               binwidth = 1.25,
               stackdir = "center",
               show.legend = FALSE) + 
  scale_fill_brewer(palette="Set1") + 
  scale_x_discrete(labels = paste(continent_count$continent, "\nn = ",continent_count$n)) +
  labs(x="Continent",y="Life expectancy",title="Life Expectancy by Continent",caption= "Source: gapminder data set") +
  geom_hline(yintercept = mean(df$lifeExp, na.rm = T) ,
             linetype = "dashed",
             color = "green",
             size = 1) + 
  theme_minimal(base_family = "Times New Roman",base_size=14) + 
  theme(plot.title = element_text(hjust=0.5,
                                  face="bold"),
        axis.title.x = element_text(face="italic"),
        axis.title.y =element_text(face="italic"),
        plot.caption =  element_text(face="italic")) + 
  ggpubr::bgcolor("#FEFEFA")

p2

Notes:

1. ggbetweenstats() is used for creating boxplots as well as computing statistical tests (such as Welsh T test, T test, ANOVA, Kruskal - Wallis, Mann-Whitney)
2. the package also computes post-hoc tests (if needed) such as Dunn test for the Kruskal-Wallis test and displays pairwise p-values

p3 <- ggbetweenstats(data=df,
               x = continent,
               y = lifeExp,
               type = "np",
               palette = "Set1") + 
  theme_minimal(base_size = 12) + 
  ggpubr::bgcolor("#FEFEFA")

p3

Notes:

1. notch=TRUE pictures 95% confidence interval around the median
2. notch is calculated by this formula: the median +/- (1.57 * Q3 - Q1)/square root of n
3. adding information on the X axis labels about the quantity of each category is possible by grouping the data (to get the count of each category) and using paste() function in the scale_x_discrete() function
4. geom_sina() is a more robust alternative to geom_point() or geom_jitter()
5. stat_summary() functions allow to picture both the mean and error bars around the mean

p4 <- ggplot(df,aes(x=continent,
             y=lifeExp)) + 
  geom_boxplot(alpha=0.75,
               notch=TRUE,
               fill="white",
               outlier.colour = "white", outlier.size = 0) + 
  scale_x_discrete(labels = paste(continent_count$continent, "\nn = ",continent_count$n)) +
  geom_violin(alpha=0.1)+
  ggforce::geom_sina(size=1.5,aes(y=lifeExp,color=continent,
                                  text = paste0("Continent: ",continent,
                                              "\nCountry: ",country,
                                              "\nLife expectancy: ",lifeExp))) + 
  stat_summary(fun.data = mean_cl_boot, 
               geom="point",
               color="blue",
               size=5,
               show.legend = FALSE)+
  stat_summary(fun.data = mean_cl_boot, 
               geom="errorbar",
               color="blue",
               size=1,
               width=0.4)+
  labs(x="Continent",y="Life expectancy",title="Life Expectancy by Continent",caption= "Source: gapminder data set") +
  #scale_fill_brewer(palette="Set1") + 
  scale_color_brewer(palette="Set1") + 
  geom_hline(yintercept = mean(df$lifeExp, na.rm = T) ,
             linetype = "dashed",
             color = "green",
             size = 1) + 
  theme_bw(base_size=14,base_family = "Times New Roman") +
  theme(plot.title = element_text(hjust=0.5,
                                  face="bold"),
        axis.title.x = element_text(face="italic"),
        axis.title.y =element_text(face="italic"),
        plot.caption =  element_text(face="italic"))+
  ggpubr::bgcolor("#FEFEFA")

p4

ggplotly(p4,tooltip = "text")